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3 Skills You Need to Succeed in Data and Analytics Today, According to Dr. Beverly

We recently kicked off our Women in DataOps series with Dr. Beverly Wright, a data and analytics thought leader with 30 years of experience. Beverly has spent many years teaching data science and analytics to undergraduates, master’s students, PhDs, and executives. She’s also spent more than a decade consulting for companies like Nielsen, another decade on the client side at companies like Cox Communications, and she continues to chair the Analytics and Data Science Society for the Technology Association of Georgia. Dr. Wright recently joined Burtch Works as Analytics Thought Leader and Executive Recruiter, where she advises data science leaders and works with data science pros to empower them to reach their full potential.

I don’t usually open a post with an entire paragraph on someone’s background, but I wanted to establish Beverly’s bona fides to be sure you take this next part seriously. Because when it comes to what traits and skills lead to success in data and analytics, Dr. Wright is plugged in. 

And if you’re expecting to hear anything about technical or quantitative skills, you’re in for a surprise. Beverly says those things are table stakes. Instead, the top three things data and analytics leaders are looking for are curiosity, a deep understanding of context, and the ability to frame a business problem. Let’s dig a little deeper.

#1 Curiosity: “The number one thing I’m hearing is curiosity,” said Beverly. “Hiring managers and leaders within this field of data science analytics are really wanting people that have natural curiosity about the data, a natural curiosity about how to solve this problem leveraging analytics. They really want data science and analytics professionals that want to know. They’re not as intrigued by talent that is waiting to be told what to do.” 

Why is curiosity so important? Data is complex, and the first answer that jumps out isn’t always the best or only one. A truly curious data scientist doesn’t settle. They dig deeper and uncover insights beyond the questions asked. 

#2 Business Understanding: Data scientists are experts in pulling big-picture insights out of data. But without an understanding of the topic at hand, it’s tough to be that curious go-getter going beyond the questions a business partner asks. As an example, Beverly shared some work she did leading a team of volunteers for a non-profit project related to opioid addiction. She shared, “Before we began the project, we started diving into the context.” The team visited a rehab facility, listened to stories of people in recovery, and learned about the facility’s treatments. They took time to get to know the whole picture. Dr. Wright says, “…and that is a second attribute that business leaders are really looking for aside from curiosity. They want you to walk a mile in the shoes of the person who’s going to be the analytic consumer…They want you to truly understand their world.”

#3 Problem Framing: When a business partner comes to a data scientist with a question, the data scientist needs to frame the problem so that it can be solved with data. They need to know what data to use, what modeling approaches might work, and so on. But according to Dr. Wright, “It seems like we have a fairly substantial lack of knowledge around problem framing.” In her expert opinion, this challenge stems from the fact that problem framing is more of an art than a science – and because there’s no one generally accepted way to do it. But if you have this talent, you’re sure to be in demand. 

So what’s the key to learning how to frame your problems? Beverly recommends the book ‘Behind Every Good Decision’ by Pianka Jain. She also thinks that hackathons, practicum courses, and experiential learning that go end to end with the process of a data science project or an analytics initiative can help develop the skill of problem framing.

Get More Data and Analytics Insights

My conversation with Beverly was wide-ranging, with so many valuable insights. Watch the complete discussion to hear:

How data scientists can advocate and elevate data in their organizations
Why there’s a trust problem with data and what caused it
How to know when you’ve won the data and analytics battle (i.e., your organization is taking data seriously, treating it and the insights that come out of it as valued assets)

And just so much more. Dr. Wright’s extensive experience and passion for data and analytics show throughout every minute of the conversation. 

Watch the Webinar

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